Malicious Url Detection

About the book: Web applications are the essential component of human life. People carry our various operations including e-commerce and online banking. The web security is a major issues in the current scenario. So it essential to detect the malicious URLs of the phishing website. It is light weight approach and prevents the user from those websites. This survey analyzes various malicious url detection method and provide a road map for new research in this area. This research work given an insite about malicious URL detection. About the author: Dr.N.Jayakanthan is an innovative teaching professional who strongly believes in being a catalyst in the learning process. He has 20 years of teaching, 10 Years of research and 3 years of Industrial experience. He holds a doctoral degree in Computer Applications from Bharathiar University, Coimbatore. He has strong knowledge of subject areas in Computer Science combined with a broad subject background, Well versed in teaching subjects like Data Structures, Algorithms, Unix/Link, Software Testing, Networking, Python, C , C++, XML , C# .Net, Java.

Cyber-physical systems (CPS) have emerged as a unifying name for systems where cyber parts (i.e., the computing and communication parts) and physical parts are tightly integrated, both in design and during operation. Such systems use computations and communication deeply embedded in and interacting with human physical processes as well as augmenting existing and adding new capabilities. As such, CPS is an integration of computation, networking, and physical processes. Embedded computers and networks monitor and control the physical processes, with feedback loops where physical processes affect computations and vice versa. The economic and societal potential of such systems is vastly greater than what has been realized, and major investments are being made worldwide to develop the technology. Artificial Intelligence Paradigms for Smart Cyber-Physical Systems focuses on the recent advances in Artificial intelligence-based approaches towards affecting secure cyber-physical systems. This book presents investigations on state-of-the-art research issues, applications, and achievements in the field of computational intelligence paradigms for CPS. Covering topics that include autonomous systems, access control, machine learning, and intrusion detection and prevention systems, this book is ideally designed for engineers, industry professionals, practitioners, scientists, managers, students, academicians, and researchers seeking current research on artificial intelligence and cyber-physical systems.

Recent years have witnessed the evolution of Artificial Intelligence AI techniques like deep learning, machine learning, pattern recognition, Natural language processing NLP , and computer vision and their revolutionary applications in the emerging smart city and industrial automation applications In this scenario, AI provides smart and efficient tools for smart energy systems to perform smart electricity generation, emergency response, and delivery The integration of renewable energy sources into the smart grid is made easier by using Artificial intelligence technologies Meanwhile, Machine Learning the subset of Artificial intelligence provides some security and privacy assessment tools to the evolving smart energy grids As Artificial Intelligence AI techniques are still remaining in the initial stage to revolutionize the way we generate, transmit and consume the energy in the smart city and industrial infrastructure

​This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.

This book constitutes the proceedings of the First International Conference on Emerging Trends in Engineering (ICETE), held at University College of Engineering and organised by the Alumni Association, University College of Engineering, Osmania University, in Hyderabad, India on 22–23 March 2019. The proceedings of the ICETE are published in three volumes, covering seven areas: Biomedical, Civil, Computer Science, Electrical & Electronics, Electronics & Communication, Mechanical, and Mining Engineering. The 215 peer-reviewed papers from around the globe present the latest state-of-the-art research, and are useful to postgraduate students, researchers, academics and industry engineers working in the respective fields. Volume 2 presents papers on the theme “Advances in Decision Sciences, Image Processing, Security and Computer Vision – International Conference on Emerging Trends in Engineering (ICETE)”. It includes state-of-the-art technical contributions in the areas of electronics and communication engineering and electrical and electronics engineering, discussing the latest sustainable developments in fields such as signal processing and communications; GNSS and VLSI; microwaves and antennas; signal, speech and image processing; power systems; and power electronics.

Get into the world of smart data security using machine learning algorithms and Python libraries Key FeaturesLearn machine learning algorithms and cybersecurity fundamentalsAutomate your daily workflow by applying use cases to many facets of securityImplement smart machine learning solutions to detect various cybersecurity problemsBook Description Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain. The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems What you will learnUse machine learning algorithms with complex datasets to implement cybersecurity conceptsImplement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problemsLearn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDAUnderstand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimesUse TensorFlow in the cybersecurity domain and implement real-world examplesLearn how machine learning and Python can be used in complex cyber issuesWho this book is for This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book

This book constitutes the proceedings of the 10th International Conference on Network and System Security, NSS 2016, held in Taipei, Taiwan, in September 2016. The 31 full and 4 short papers presented in this volume were carefully reviewed and selected from 105 submissions. They were organized in topical sections named: authentication mechanism; cloud computing security; data mining for security application; privacy-preserving technologies; network security and forensics; searchable encryption; security policy and access control; security protocols, symmetric key cryptography; system security; Web security. The volume also contains one invited paper.

Vertical and Topical Area Tracks on AI driven IoT from Edge to Cloud and Applications